Road traffic inflicts devastating mortality on the endangered Florida panther (Puma concolor coryi). There are an estimated 220-250 adult panthers that remain, and 26 panthers were killed on roads last year. This level of mortality is unsustainable in this recovering species and demands targeted efforts to reduce and prevent animal-vehicle collisions. Wildlife underpasses can increase safe travel for both drivers and wildlife, but installation of crossings is a costly endeavor that requires proper planning. We conducted a camera trap experiment in an effort to understand connectivity patterns in the Florida panther and other terrestrial wildlife in south Florida. The goal of this connectivity study was to identify target locations for wildlife crossing installation in an effort to mitigate road-related panther mortality. We installed 75 camera traps at 16 sites across a 5 km segment of Keri Rd in the Okaloacoochee Slough State Forest. Because wildlife crossings should ultimately benefit multiple species, we approached our question by developing mutispecies occupancy models (OM) where "occupancy" was defined as the probability of being captured by a camera trap. We collected and tagged >27,000 photos of wildlife during the study period (Dec 2017- May 2019); the most common species photographed were deer (>17,000 photos), turkey (>3,600 photos), and FL panthers (>1,400 photos). Data were then organized using Digikam and OM models were built in the R packages "CamtrapR" and "rjags". We used season, habitat type, and distance to the nearest access road as covariates in our models, and cross-validated OM models with historical roadkill and telemetry data in our study area. By identifying target locations for underpasses, the results from this study have immediate management applications in ecology and transportation planning. As landscape-level anthropogenic disturbance increases, mitigating the negative effects of roads on wildlife and allowing safe passage for drivers will continue to be an important issue worthy of careful planning and data-driven solutions.